If someone has the genetic mutations, they can be treated with drugs or have a defibrillator implanted in their chest. But how do you work out who is at risk? Genetic tests can help but not everyone with the altered genes seems to have the syndrome. Electrocardiograms or ECGs can measure the heart’s electrical activity, but exactly how features on the ECG relate to risk is not fully understood.

All in the t-wave

Enter the virtual heart. By running hundreds of genetically customised hearts on a supercomputer, each for many thousands of beats, Adam Hill and his colleagues from the Victor Change Cardiac Research Institute in Sydney, Australia, have cracked some of the secrets of SADS.

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One sign that someone has the genetic condition that most commonly leads to SADS, known as long QT syndrome, is a distinctive bump or notched t-wave in their ECG readout. “For the past 30 years, that notched t-wave has been in the diagnostic criteria but nobody’s known what’s caused it,” says Hill. “We show what causes it.”

With the wealth of virtual data created by running the simulations, they were able to establish that the more extreme the bump in the ECG is, the higher a person’s risk of dying. What’s more, they found the main genes thought to cause the problem can be either amplified or compensated for by complex combinations of other genes.

Better diagnosis

“We show that the degree of t-wave notching is correlated with how much risk they are at,” says team member Arash Sadrieh. “So person A can have the mutation [but his ECG shows] he’s absolutely normal, so you don’t need to do the complex surgery to prevent sudden cardiac death. And if his sister has a more notched t-wave, then she is at more risk.”

It would have been impractical to use real hearts for this research as you’d need huge numbers of people with specific genetic combinations, all with their full genome sequenced, hooked up to an ECG for days.

Hill says the team has taken the virtual trial data, applied it to patient records of ECGs and found the finer grained analysis of the ECG led to more accurate diagnoses. They’re also making progress using the simulations to distinguish between different types of long QT syndrome.

“The work is quite a milestone in terms of how thoroughly they’ve investigated this issue of the notched t-wave…and how you interpret it,” says Peter Hunter from the University of Auckland in New Zealand, one of the world’s leading cardiac modelling experts. “This has pushed it to a new level.”